Housing insecurity and Black-white residential segregation
Where Housing insecurity is higher, Black-white residential segregation tends to be lower. The link is weak: -0.35 across 1,518 counties, on a scale from −1 (opposite) to +1 (in step). That figure compares places with the same population density, income and education, so those differences can't explain it. It holds inside states too. Measured separately within each of 23 states, the middle value of the link is -0.02.
Holds after adjusting
Every place, plotted
One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.
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What each measure is
Housing insecurity
The estimated percentage of adults who were unable to pay rent or mortgage on time in the past year. It is adjusted so places with older or younger populations can be compared fairly. It is an estimate from a statistical model, not a direct count from a local survey.
CDC PLACES · PLACES HOUSINSECU, age-adjusted
Black-white residential segregation
How unevenly Black and white residents are spread across the county's neighborhoods, from 0 (evenly mixed) to 100 (completely separate). It is the share of either group who would have to move for the two groups to be spread the same way. It is only calculated where both groups live in large enough numbers.
County Health Rankings · County Health Rankings v141
Highest and lowest
Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.
Counties
By housing insecurity
| Housing insecurity | Black-white residential segregation | |
|---|---|---|
| Highest | ||
| East Carroll Parish, LA | 33.6% | 59.5 |
| Holmes County, MS | 32.5% | 22.1 |
| Humphreys County, MS | 32.1% | 24.2 |
| Greene County, AL | 31.8% | 27.1 |
| Tunica County, MS | 31.7% | 25.5 |
| Lowest | ||
| Falls Church city, VA | 5.9% | 17.4 |
| Arlington County, VA | 6.9% | 51.1 |
| Los Alamos County, NM | 6.9% | 49 |
| Hamilton County, IN | 6.9% | 37.2 |
| Ozaukee County, WI | 7.2% | 40.7 |
By black-white residential segregation
| Housing insecurity | Black-white residential segregation | |
|---|---|---|
| Highest | ||
| Manistee County, MI | 12.5% | 90.2 |
| Cass County, IN | 14.2% | 88.9 |
| Livingston County, MO | 13.7% | 88.5 |
| Kootenai County, ID | 10% | 88.3 |
| Orange County, IN | 12.4% | 87.5 |
| Lowest | ||
| St. Helena Parish, LA | 24.7% | 1.44 |
| Surry County, VA | 14.7% | 1.93 |
| Clinch County, GA | 20.7% | 2 |
| Jenkins County, GA | 23.7% | 2.27 |
| Stewart County, GA | 26.1% | 3.4 |
States — Housing insecurity is not published for states
By black-white residential segregation
| Housing insecurity | Black-white residential segregation | |
|---|---|---|
| Highest | ||
| Montana | — | 80.4 |
| Idaho | — | 77 |
| Wisconsin | — | 76.7 |
| New York | — | 75.1 |
| Maine | — | 74.9 |
| Lowest | ||
| Delaware | — | 44.8 |
| South Carolina | — | 48.2 |
| Nevada | — | 50.7 |
| Mississippi | — | 51.1 |
| Virginia | — | 51.2 |
Metro areas — Black-white residential segregation is not published for metro areas
By housing insecurity
| Housing insecurity | Black-white residential segregation | |
|---|---|---|
| Highest | ||
| Gallup, NM | 30.2% | — |
| Clarksdale, MS | 29.8% | — |
| Greenville, MS | 28.1% | — |
| Deming, NM | 26.5% | — |
| Selma, AL | 26.5% | — |
| Lowest | ||
| Los Alamos, NM | 6.9% | — |
| Bozeman, MT | 7.5% | — |
| Heber, UT | 7.6% | — |
| Bismarck, ND | 8.31% | — |
| Pella, IA | 8.4% | — |
Cities and towns — Black-white residential segregation is not published for cities and towns
By housing insecurity
| Housing insecurity | Black-white residential segregation | |
|---|---|---|
| Highest | ||
| Benton Harbor city, MI | 38.8% | — |
| Lamont CDP, CA | 38.8% | — |
| East Bakersfield CDP, CA | 38.7% | — |
| Glasgow Village CDP, MO | 38.3% | — |
| Tallulah city, LA | 37.4% | — |
| Lowest | ||
| Great Falls CDP, VA | 4.7% | — |
| Difficult Run CDP, VA | 4.8% | — |
| Mountain Brook city, AL | 4.9% | — |
| Huntington Woods city, MI | 5% | — |
| Whitefish Bay village, WI | 5.1% | — |
Counties furthest from the pattern
Compared with the straight line that best fits all 1,520 counties: the five with far more black-white residential segregation than their housing insecurity would suggest, and the five with far less.
| Housing insecurity | Black-white residential segregation | |
|---|---|---|
| Above the line | ||
| Apache County, AZ | 25.3% | 80.6 |
| Cibola County, NM | 22.5% | 83 |
| Cass County, IN | 14.2% | 88.9 |
| Manistee County, MI | 12.5% | 90.2 |
| Livingston County, MO | 13.7% | 88.5 |
| Below the line | ||
| Clarke County, VA | 9% | 8.58 |
| Pawnee County, KS | 12.4% | 4.44 |
| Surry County, VA | 14.7% | 1.93 |
| Rappahannock County, VA | 10.1% | 8.37 |
| Camden County, NC | 9.8% | 8.9 |
Two series, one county
Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.
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Every version of the link
Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.
| Before adjusting for anything | -0.363 | 1,518 counties reporting both |
| After adjusting for density, income and education | -0.352 | the part of the link that is not just how urban, rich and educated a place is |
| Also adjusting for population size | -0.381 | size taken out as well as density |
| Also comparing only within each state | -0.255 | each county is compared only with others in its own state, so this is no longer a comparison between states |
| Giving bigger counties more weight | -0.133 | the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 175 equally weighted counties |
| Middle value inside single states | -0.021 | the link worked out inside each of 23 states with at least 20 counties reporting |
| Using ranks, after adjusting | -0.281 | uses each county’s rank, not its value, so a few extreme counties cannot create the link |
How much to believe it
Could it be chance?
The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 1.7e-45. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 3.7e-6. The site tested 20,910 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 8.7e-45.
Do nearby places look alike?
Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.36 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.
Did they change together?
Not measurable: at least one of these is published for too few of the years a change needs (2014–2019 or 2019–2023), or for too few counties in both.
Related pairs
- Housing insecurity and Returns claiming the earned income credit — +0.83
- Housing insecurity and Children in single-parent households — +0.73
- Housing insecurity and Average test score — -0.71
- Housing insecurity and Social connection score — -0.69
- Housing insecurity and Homicide rate — +0.68
- Housing insecurity and Economic connectedness — -0.65
- Housing insecurity and Republican share of the two-party vote, 2020 — -0.62
- Housing insecurity and Republican share of the two-party vote, 2016 — -0.62
Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Housing insecurity and Black-white residential segregation